File size: 2,928 Bytes
ebae4cc e710031 ebae4cc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Covid Dialog dataset in English and Chinese"""
import copy
import os
import re
import textwrap
import json
import datasets
# BibTeX citation
_CITATION = """
"""
# Official description of the dataset
_DESCRIPTION = textwrap.dedent(
"""
"""
)
# Link to an official homepage for the dataset here
_HOMEPAGE = ""
_LICENSE = ""
import datasets
import os
import json
names = ["all", "assignment", "grouping", "miscellaneous", "ordering"]
class LsatQA(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=_DESCRIPTION) for name in names]
def _info(self):
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"references": datasets.Sequence(datasets.Value("string")),
"gold_index": datasets.Value("int64"),
}
)
return datasets.DatasetInfo(
description=f"LSAT QA dataset, as preprocessed and shuffled in HELM",
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
test = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
train = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
val = dl_manager.download(os.path.join(self.config.name, "valid.jsonl"))
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"file": train},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"file": val},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"file": test},
),
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, file):
with open(file, encoding="utf-8") as f:
for ix, line in enumerate(f):
yield ix, json.loads(line)
|